Apply Anthropic Skill Best Practices

# Anthropic's official skill authoring best practices

Apply Anthropic's official skill authoring best practices to your skill.

Good Skills are concise, well-structured, and tested with real usage. This guide provides practical authoring decisions to help you write Skills that Claude can discover and use effectively.

## Core principles

### Skill Metadata

Not every token in your Skill has an immediate cost. At startup, only the metadata (name and description) from all Skills is pre-loaded. Claude reads SKILL.md only when the Skill becomes relevant, and reads additional files only as needed. However, being concise in SKILL.md still matters: once Claude loads it, every token competes with conversation history and other context.

### Test with all models you plan to use

Skills act as additions to models, so effectiveness depends on the underlying model. Test your Skill with all the models you plan to use it with.

**Testing considerations by model**:

- **Claude Haiku** (fast, economical): Does the Skill provide enough guidance?
- **Claude Sonnet** (balanced): Is the Skill clear and efficient?
- **Claude Opus** (powerful reasoning): Does the Skill avoid over-explaining?

What works perfectly for Opus might need more detail for Haiku. If you plan to use your Skill across multiple models, aim for instructions that work well with all of them.

## Skill structure

<Note>
  **YAML Frontmatter**: The SKILL.md frontmatter supports two fields:

- `name` - Human-readable name of the Skill (64 characters maximum)
- `description` - One-line description of what the Skill does and when to use it (1024 characters maximum)

  For complete Skill structure details, see the [Skills overview](docs.claude.com/en/docs/agents-and-tools/agent-skills/overview#skill-structure).
</Note>

### Naming conventions

Use consistent naming patterns to make Skills easier to reference and discuss. We recommend using **gerund form** (verb + -ing) for Skill names, as this clearly describes the activity or capability the Skill provides.

**Good naming examples (gerund form)**:

- "Processing PDFs"
- "Analyzing spreadsheets"
- "Managing databases"
- "Testing code"
- "Writing documentation"

**Acceptable alternatives**:

- Noun phrases: "PDF Processing", "Spreadsheet Analysis"
- Action-oriented: "Process PDFs", "Analyze Spreadsheets"

**Avoid**:

- Vague names: "Helper", "Utils", "Tools"
- Overly generic: "Documents", "Data", "Files"
- Inconsistent patterns within your skill collection

Consistent naming makes it easier to:

- Reference Skills in documentation and conversations
- Understand what a Skill does at a glance
- Organize and search through multiple Skills
- Maintain a professional, cohesive skill library

### Writing effective descriptions

The `description` field enables Skill discovery and should include both what the Skill does and when to use it.

<Warning>
  **Always write in third person**. The description is injected into the system prompt, and inconsistent point-of-view can cause discovery problems.

- **Good:** "Processes Excel files and generates reports"
- **Avoid:** "I can help you process Excel files"
- **Avoid:** "You can use this to process Excel files"
</Warning>

**Be specific and include key terms**. Include both what the Skill does and specific triggers/contexts for when to use it.

Each Skill has exactly one description field. The description is critical for skill selection: Claude uses it to choose the right Skill from potentially 100+ available Skills. Your description must provide enough detail for Claude to know when to select this Skill, while the rest of SKILL.md provides the implementation details.

Effective examples:

**PDF Processing skill:**

```yaml  theme